Prediction of IDP Structural Ensembles with NMR-Assisted Artificial Intelligence

This research proposal outlines a collaborative initiative between Swedish and Korean principal investigators to enhance the understanding and prediction of Intrinsically Disordered Proteins (IDPs) using cutting-edge artificial intelligence (AI) and Nuclear Magnetic Resonance (NMR) methodologies.

The primary objective is to develop a generative AI model capable of accurately predicting the conformational ensemble of IDPs under various conditions. This initiative will also involve the creation of innovative NMR techniques to validate these predictions rigorously.

The research leverages the complementary expertise of the Swedish team´s proficiency in AI and machine learning applications in biomolecular NMR, alongside the Korean team´s advanced NMR methodological developments for high-resolution IDP analysis. The project aims to merge these strengths to predict and validate IDP structural ensembles with unprecedented accuracy.

Novel experimental NMR techniques will be developed, including the development of laser-driven approaches for the measurement of long-range contacts within IDPs.

This international collaboration will not only push the boundaries of AI and NMR technologies but also facilitate the transfer of knowledge and techniques between Sweden and Korea, potentially leading to significant breakthroughs in understanding protein dynamics and interactions relevant to health and disease.